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spout 0.1.5

Spout is a small and simple framework that makes it easy to work with data
streams in Python. In particular, Spout was designed with the processing and
consumption of live data sources in mind.

How it works

At the heart of Spout is the concept of a Stream (which is defined in an
abstract Stream class). This defines the basic operations that can be
performed upon a data stream:

Mapping

The items in one stream can be “mapped” to another stream. This is done by
applying a supplied Function to each item in the input stream, to produce
another output stream.

stream.map(Function)

Filtering

The items in a stream can be “filtered”, so that the resultant stream only
contains items that match a given criteria. This is done by using a supplied
Predicate to test each item in the input stream, and copies it to the output
stream if it passes the test criteria.

stream.filter(Predicate)

Processing (Consuming)

The items in a stream are used in some calculations or functionality that
provides no further output to the stream. This is done by applying the supplied
Operation to each item in the stream.

stream.for_each(Operation)

Usage

To use Spout, you first need to create an input data stream. A data stream is simply an
instantiation of a Stream or any of its children (which can be found in the
streams.py file). The Stream class has been specifically designed so that it
is easy to extend and wrap around currently existing data sources that you might
have, such as files or databases.

Some existing examples of stream data sources can by found in sources.py.

For example, to create a Stream out of the lines in a plain text file:

Now that you have your data in a stream, you simply have to process it! This can
be done by creating and using your own Functions, Predicates or Operations
(see above).

For example, to print out all the lines in a text file that start with a digit,
but with the digit stripped, we can create our own Predicate and Function
and pass these to the .filter() and .map() functions: